Machine learning technology in domains with high social impact such as health, law, and finance, should be handled with particular care. Beyond test accuracy, one must make sure that additional social constraints are met.
For instance, when deciding if to hire an individual, it may be the case that, for the collected data, a particular racial group exhibits higher positive outcomes resulting in an unfair model [1]}, [2]}, [3]}. One must also ensure that the false positive and false negative rates are roughly similar across ethnic groups [4]}.
